Introduction to Special Issue

Abstract

The history of chest auscultation by unaided ears goes back to almost 2000 years ago. But the discovery and use of respiratory lung sounds as indicators of health and disease began with Laennec, who formalized the relationship between human pulmonary diseases and respiratory auscultation in 1819. He then invented stethoscope in 1921. Stethoscope enabled physicians to listen to respiratory sounds of their patients and detect any symptomatic signs. Modern technology can help physicians even more these days. Breath sound analysis using digital signal processing techniques has recently drawn much attention because of its diagnostic capabilities. The articles in this special issue focus on how computerized respiratory sound analysis can quantify changes in lung sounds, store records of the measurements made, de-noise the signals of interest from any artifacts and interference, and produce graphical representations of characteristic features of the respiratory sounds to help with the diagnosis and treatment of patients suffering from lung diseases. Ray Murphy reviews the combined use of stethoscope and computerized lung sound analysis in the clinical assessment of lung infectious diseases in the first paper published in this volume. One issue of interest for both physicians and researchers in this field is to find features which best describe the relationship between the respiratory flow and the lung sounds of patients compared to that of healthy individuals. Since lung sounds have relatively low frequency and low intensity, it is crucial to remove the noise and other interfering sounds (i.e., heart sounds) from the lung sounds prior to any diagnostic analysis. Many researchers around the world have been involved in this research applying linear and nonlinear digital signal processing techniques to develop novel methods that remove adventitious sounds form the lung sound record. The paper by Gnitecki and Moussavi reviews a number of heart sound cancellation methods, and the authors discuss some advantages and problems associated with different methods. Adventitious lung sounds that are of diagnostic value include crackles, wheezes, squawks, rhonchi, and stridor. Out of these sounds, detection of crackles (both fine and coarse) is more important because of its diagnostic values at the early stages of disease. Nowadays specialists rely on computer aided analysis to count the number of crackles at different locations of chest. Hence, this area of research is concerned with developing more accurate and efficient methods for detecting crackles. The next two papers by Hadjileontiadis and Charleston et al. present two methods for crackle detection using empirical mode decomposition and fractal dimension analysis.